Drunkard's Walk is a mathematical idea involving a random iterative traversal of a multidimensional space.

Drunkard's Rock is an experiment I did to pursue a random iterative traversal of the multidimensional musical artist-similarity space.

In the mathematical version, the drunkard is allowed to retrace their steps, and in fact the point of the problem is to determine the chance of the drunkard randomly arriving home again.

In my version, retracing steps is explicitly disallowed, and thus the drunkard is doomed to wander until the universe expires. Probably it says something about my personality that this seems like the preferable curse to me.

Anyway, I started the calculation with Black Sabbath, both because my own musical evolution sort of started in earnest with Black Sabbath, and because Paul Lamere used Black Sabbath as the reference point in his inversely minded Six Degrees of Black Sabbath, which attempts to find the shortest path between two bands.

My version, to reiterate, just keeps wandering. I guess it is searching for the longest path between Black Sabbath and whatever it finds last. Except I stopped it at 100k steps, because the resulting web page is enormous enough. It will annoy you least if you just leave it alone for a couple minutes while it loads, and then you should be able to scroll around.

Every Noise at Once is a readability-adjusted scatter-plot of musical genres. The music moves from high density on the left to high bounciness on the right, and from high mechanism at the top to high organism at the bottom. Although I do have more words to explain what each of these ideas means, it's maybe better to just hear how the qualities manifest themselves in actual music.

So here are four data-generated sampler playlists of songs that demonstrate the extreme values of these two analytical dimensions:

Meanwhile, one thing I did with our Massive Amounts of Data today is make some playlists of quiet, calm music from unlikely sources. Here, for example, are three sets from artists normally known for metal, electronica or hip hop.

I gave a talk on music discovery and genre-mapping at the 2014 EMP Pop Conference in Seattle last weekend. My co-panelist Michaelangelo Matos had the presence of mind to record the audio from this, and mostly the talk was just audio. Actually, I was wearing some really excellent silver pants, but while talking I was behind a podium, so you aren't missing that much. The map I describe at the end is Every Noise at Once.

So if you're curious, the talk is 16:32 long, and you can listen here:

Music is the thing humans do best, and all the astonishing music in the world, or close enough, is now available online. This is basically more awesome than the grandest future I ever imagined as a kid.

But that's a lot of music. How do we make any kind of sense of it, so that this vast theoretical grandness can have any kind of actual practical significance? How do you listen to anything when you can suddenly hear every noise at once?

Those are questions I am paid to try to help answer. I've been working for a small music-intelligence startup in Somerville called The Echo Nest. We've been running the back-end data-analysis systems that supply recommendations, personalization and music-discovery ideas to a bunch of streaming music services. When I tell people this, they usually say "Like Spotify?" And I say "Yes, like Spotify."

But although we've been working with Spotify in various capacities, and various non-Spotify developers have made applications that combine our things with Spotify's music, we haven't been running the parts of Spotify that we run for other services. This has been an ongoing personal frustration, because Spotify is the most visible on-demand streaming music service in the world, and I've been pretty convinced that we could help them do a dramatically better job.

We are now going to get that chance. The Echo Nest has, in fact, just been wholly acquired by Spotify. Starting today, it's actually my job to try to improve essentially everything about Spotify that matters to me.

And this is only barely the beginning. I think we are, I mean collectively as humanity, only just at the dawn of the era of infinite music. The current streaming-music interaction-models and feature-sets are as much vestiges of our past technical constraints as anything else. It's as if we have jumped from the horse-drawn carriage to the free personal teleporter, suddenly, without the intervening benefit of even basic maps, never mind language translators or cultural history or GPS.

For the world of music to become something we actually inhabit, natively, as opposed to a bunch of awkward phone icons into which we try to contort our curiosity and wonder, or a vast unknown from which we cower and seek familiar comfortable retreats, it's going to take a lot more than "Play me more stuff like Dave Matthews, but do a better job of it." It's going to require that we belatedly render this vast world navigable, and chart it accurately and compellingly, and put sensible enough control panels on the teleporters that you have some prayer of not just constantly zapping yourself 60' deep into an exotic undiscovered faraway cliff face.

So that's what I'm going to be working on now.

[PS: I no longer remember anything memorable or inspiring or even intelligible anybody ever said to introduce my previous acquisitions, but by way of explaining the Echo Nest purchase, Spotify CEO Daniel Ek said this: "At Spotify, we want to get people to listen to more music."]

[PPS: And it's going to take a little while to get Echo Nest + Spotify things actually hooked up and working, but here's some music to listen to in the meantime.]

Some of these are kind of duh, like "chicago house" being the top genre for Chicago. But as always in data-anything, some obviousness is what gives us the courage to believe the things we didn't already think.

On a plane flight to Dallas for the funeral of one of my dearest and nearest-to-life-long friends, I distracted myself from sadness and terror by prodding some music out of my iPad. On the way back home I wrote some words to go with it, fragments of a song of remembrance, or at least of imagination in absentia. Later, after Bethany pointed out that for once I'd written too few words, I wrote some more. Today I sang them, over and over again.

Those of you who have not before listened to any of my own music should be warned that it is cheerfully devoid of technical virtues, but for the moment I have chosen to treat this as a style.

Those of you who did not know Tex are really not at much of a disadvantage for understanding what is going on in the song, but you missed one of the most unforgettable and unmistakable people I ever met, and one who carried me, at times literally, through much of my childhood. He deserves far better than this maudlin, lurching song, but once you're dead you can't do anything about the ways people make up to miss you.